About: Chest Computed Tomography for the Diagnosis of Patients with Coronavirus Disease 2019 (COVID-19): A Rapid Review and Meta-Analysis

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Chest Computed Tomography for the Diagnosis of Patients with Coronavirus Disease 2019 (COVID-19): A Rapid Review and Meta-Analysis
Creator	Li, Wei Liu, Enmei Luo, Zhengxiu Chen, Xin Wang, Xiaohui Wang, Ling Chen, Yaolong Yang, Nan Lee, Myeong Lei, Junqiang Tian, Jinhui Ahn, Hyeong Fukuoka, Toshio Luo, Xufei Lv, Meng Ma, Yanfang Zhang, Xianzhuo Liu, Yunlan Ren, Mengjuan Wang, Mengshu
source	MedRxiv
abstract	Background: The outbreak of the coronavirus disease 2019 (COVID-19) has had a massive impact on the whole world. Computed tomography (CT) has been widely used in the diagnosis of this novel pneumonia. This study aims to understand the role of CT for the diagnosis and the main imaging manifestations of patients with COVID-19. Methods: We conducted a rapid review and meta-analysis on studies about the use of chest CT for the diagnosis of COVID-19. We comprehensively searched databases and preprint servers on chest CT for patients with COVID-19 between 1 January 2020 and 31 March 2020. The primary outcome was the sensitivity of chest CT imaging. We also conducted subgroup analyses and evaluated the quality of evidence using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Results: A total of 104 studies with 5694 patients were included. Using RT-PCR results as reference, a meta-analysis based on 64 studies estimated the sensitivity of chest CT imaging in COVID-19 was 99% (95% CI, 0.97-1.00). If case reports were excluded, the sensitivity in case series was 96% (95% CI, 0.93-0.99). The sensitivity of CT scan in confirmed patients under 18 years old was only 66% (95% CI, 0.11-1.00). The most common imaging manifestation was ground-glass opacities (GGO) which was found in 75% (95% CI, 0.68-0.82) of the patients. The pooled probability of bilateral involvement was 84% (95% CI, 0.81-0.88). The most commonly involved lobes were the right lower lobe (84%, 95% CI, 0.78-0.90) and left lower lobe (81%, 95% CI, 0.74-0.87). The quality of evidence was low across all outcomes. Conclusions: In conclusion, this meta-analysis indicated that chest CT scan had a high sensitivity in diagnosis of patients with COVID-19. Therefore, CT can potentially be used to assist in the diagnosis of COVID-19.
has issue date	2020-04-17(xsd:dateTime)
bibo:doi	10.1101/2020.04.14.20064733
has license	medrxiv
sha1sum (hex)	e3f209f007921fcbe574781b183e4501183ff907
schema:url	https://doi.org/10.1101/2020.04.14.20064733
resource representing a document's title	Chest Computed Tomography for the Diagnosis of Patients with Coronavirus Disease 2019 (COVID-19): A Rapid Review and Meta-Analysis
resource representing a document's body	covid:e3f209f007921fcbe574781b183e4501183ff907#body_text
is schema:about of	named entity 'diagnosis' named entity 'coronavirus disease 2019' named entity 'Disease' named entity 'IMPACT' named entity 'ROLE' named entity 'imaging' named entity 'Computed tomography' named entity 'outbreak of the coronavirus' named entity 'Computed Tomography' named entity 'COVID' named entity 'Title Page' named entity 'medRxiv' named entity 'CT imaging' named entity 'peer review' named entity 'COVID-19' named entity 'COVID-19' named entity 'RT-PCR' named entity 'preprint' named entity 'medRxiv' named entity 'peer review' named entity 'preprint' named entity 'CT imaging' named entity 'meta-analysis' named entity 'virus' named entity 'nucleic acid test' named entity 'preprint' named entity 'meta-analyses' named entity '5.7' named entity 'preprint' named entity 'coronavirus' named entity 'follow-up' named entity 'peer review' named entity 'peer review' named entity 'preprint' named entity 'nucleic acid' named entity 'case series' named entity 'medRxiv' named entity 'preprint' named entity 'preprint' named entity 'preprint' named entity 'case-control studies' named entity 'COVID-19.' named entity 'preprint' named entity 'meta-analyses' named entity 'COVID-19' named entity 'fatigue' named entity 'peer review' named entity 'infection' named entity 'preprint' named entity 'preprint' named entity 'case series' named entity 'Subgroup analyses' named entity 'COVID-19' named entity 'case reports' named entity 'Wuhan seafood market' named entity 'peer review' named entity 'World Health Organization' named entity 'case series' named entity 'preprint' named entity 'preprint' named entity '11 March 2020' named entity 'medRxiv' named entity 'heterogeneity' named entity 'follow-up' named entity 'myalgia' named entity 'chest CT'

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